Twenty years after Dr. Holonyak's invention, a compact disc (CD) was introduced to the market in 1982. A laser diode is always in the heart of optical storage systems and a variety of other industrial applications. Innovations in laser diode technologies have brought optical storage evolutions from CD to digital versatile disc (DVD) and then Blu-ray disc (BD) every ten years. Since the most important reason for our success in laser development is our choice of metalorganic chemical vapor deposition (MOCVD) for growing these semiconductor alloys, MOCVD equipment, growth conditions, material properties, and phenomena associated with MOCVD and various alloy lasers grown by MOCVD are described in detail. Reviewing the development history would tell us how the laser diode has created a huge market and why recent innovations will predict future applications.

Abstract Merging computer‐generated objects onto a human video sequence is an important technique for many applications such as augmented reality and special effects in movies. In this paper, we propose a new method for merging virtual objects onto the human video sequence. First, we track the current 3D pose of the human body by using spatio‐temporal analysis. Then we generate CG objects and merge them with the human body in video. In this paper, we demonstrate examples of merging virtual cloth with the video‐captured images. Copyright © 2001 John Wiley & Sons, Ltd.

This paper describes a new method for tracking of a human body in 3D motion by using constraints imposed on the body from the scene. An image-based approach for tracking exclusively uses a geometrical model of the human body. Since the model usually has a large number of degrees of freedom (DOF), a chance to be corrupted by noise increases during the tracking process, and the tracking may fall in an ill-posed problem. To cope with this problem, we pay our attention to that a human body cannot move freely, and usually receive some constraints a from the scene. The new method uses constraints imposed on position, velocity and acceleration of the part of the body from the scene. These constraints can reduce the DOF of the model. This reduction guarantees the tracking problem to be a well-posed problem, and prevents tracking errors by noise. Experiments with real image sequences support a precise tracking of the body.

The model-based approaches for tracking of human bodies in image sequences can be categorised into two types; fitting model to body frame by frame, and accumulating estimated pose displacements in successive frames after model fitting at the initial frame. The latter has an inherent drawback as accumulation of tracking errors while the one has a great advantage as small computational efforts compared with the former. This paper proposes a new method which can correct the tracking errors by propagation from fitting model to body at a few key-frames. The propagation makes it possible to establish tracking of bodies under occlusion. Capturing the actor's motions in real old movies is presented.

Merging virtual object onto human video sequence is an important technique for many applications such as special effects in movies and augmented reality applications. In a traditional method, the operator manually fit 3D body model onto the human video sequence, and generate virtual objects at the current 3D body pose. However, the manual fitting is a time consuming task, and the automatic registration is required. In this paper, we propose a new method for merging virtual objects onto the human video sequence. First, we track the current 3D pose of human figure by using the spatio-temporal analysis and the structural knowledge of human body. Then we generate computer-generated objects and merge it with the human figure in video. In this paper, we demonstrate examples of merging virtual cloth with the video captured images.

This paper describes a novel method for gesture recognition using character recognition techniques on two-dimensional eigenspace. An image-based approach can capture human body poses in 3D motion from multiple image sequences. The sequence of poses can be reduced into a trajectory on the two-dimensional eigenspace with preserving the main features in gesture, so that the gesture recognition equals the character recognition. Experiments for the gesture recognition using some character recognition techniques show our method is useful.

This paper proposes a new method for model-based tracking of a human body in 3D motion from multiple views. The tracking is performed by estimating the pose increment of the body parts from multiple image sequences after establishing of fitting an articulated model to the human body at the initial frame. The pose increment can be obtained from solving a system of linear equations. This calculation does not depend on the number of view points. Experiments verify that the proposed method can avoid occlusion and visual degenerate from a particular view point, and track a human body in complicated motion.

We first discuss the position of cameras and displays in digital television systems. It is difficult to realize these devices in digital form so cameras and displays will remain analog for some time, even after television signal processing is implemented digitally. Nevertheless, the importance of camera and display in television systems will not diminish. These devices will always be key elements in the human interface. Second, we describe the current state of the art and future trends in camera and display technology. In addition to providing an overview of the charge coupled device (CCD), we discuss the digital technologies used in a CCD camera. We also provide an overview of currently available displays-CRT's, flat panel displays, projection displays, and head-mounted displays (HMD's)-and discuss future possible lines of research. Finally, we discuss camera and display technology as applied to digital television systems, including the use of these devices in a multimedia environment.>

A method of estimating range flow (space displacement vector field) on nonrigid as well as rigid objects from a sequence of range images is described. This method can directly estimate the deformable motion parameters by solving a system of linear equations that are obtained from substituting a linear transformation of nonrigid objects expressed by the Jacobian matrix into motion constraints based on an extension of the conventional scheme used in intensity image sequences. The range flow is directly computed by substituting these estimated motion parameters into the linear transformation. The algorithm is supported by experimental estimations of range flow on a sheet of paper, a piece of cloth, human skin, and a rubber balloon being inflated, using real range image sequences acquired by a video rate range camera.>

A model-based method for analyzing a human body motion is presented. The method is based on a robot arm model which represents a human body motion. Combining the model and the gradient scheme, the movement of the configuration of the model (Human) can be directly estimated from an image sequence.>

A dynamic depth extraction method (DDEM) is proposed, which tracks the time taken for a detected edge to move a known distance on the image plane and hence is able to calculate depth. Experimental results for three vertical bars of differing depth show the mean depths obtained were almost the same as those obtained from direct measurement. The fluctuation of obtained depth was about 3.6%, which corresponds to one half frame difference in matching time of the near bar. The DDEM was also successfully applied to a complicated room.>

A method is described for estimating range flow (space displacement vector field) on a nonrigid object as well as a rigid object from a sequence of range images. The method can directly estimate the deformable motion parameters by solving a system of linear equations which are obtained by substituting a linear transformation of a nonrigid object expressed by a Jacobian matrix into motion constraints based on an extension of the conventional scheme used in intensity image sequences, and the range flow is obtained from the motion parameters and linear transformation. The algorithm is supported by experiments of motion estimation of a sheet of paper, a piece of cloth, the movement of human skin, and the motion of a rubber balloon being inflated using real range image sequences acquired by a video rate range finder. Furthermore, it is shown that by adding the intensity image sequence to the range information, one can prevent the equation system from falling in an ill-posed condition.>

The author proposes a segmentation method based on the gradient method for multiple moving objects which may include an object for which a unique interpretation of the motion is difficult. By the gradient method, the 3-D motion parameters of a rigid object can be estimated without determining correspondence as a pseudoinverse solution for a system of linear equations if the 3-D structure of the object is already given. Based on the residual square-error in the motion estimation, the image is segmented if it contains regions with different motions. If the motions are recognized as the same, the regions are merged. Thus, the object is extracted by iterating the segmentation and merge on the image.>

The necessary and sufficient conditions that an object should satisfy so that motion can be uniquely determined by a direct method are discussed. This direct method, based on the temporal-spatial gradient scheme, can estimate the three-dimensional (3-) motion parameters of a rigid moving object from an image sequence, by utilizing depth information of the object. It is shown that the 3-D motion cannot be uniquely determined for only eight kinds of objects with special geometric structure and surface pattern.>